Device and method for processing signals from a set of ultrasonic transducers

ABSTRACT

A processing system for processing signals from a plurality of transducers of an ultrasonic sensor in order to determine characteristic information relating to an object detected by the ultrasonic sensor is provided. The system comprises a coupling device for transforming the signals received from the transducers into pulses, and a pulse processing unit for determining the characteristic information based on the pulses delivered by the coupling device. The coupling device comprises: a thresholding unit for applying, for each signal received from a transducer, thresholding to a signal derived from the signal received from the transducer and extracting directional information contained in the phase of the derived signal; a transformation unit for transforming the derived signal into pulses containing the phase of the signal, using the information extracted by the thresholding unit.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims priority to foreign French patent applicationNo. FR 2104297, filed on Apr. 26, 2021, the disclosure of which isincorporated by reference in its entirety.

FIELD OF THE INVENTION

The invention relates in general to the field of detection systems, andin particular to a device and a method for processing signals from a setof ultrasonic transducers.

BACKGROUND

Ultrasonic sensors are nowadays used in numerous applications such asspatial localization, gesture detection, fingerprint recognition,biomedical images, etc.

An ultrasonic sensor emits short high-frequency ultrasonic signals atregular intervals or continuously. These pulses propagate through theair at the speed of sound. When they encounter an object, they arereflected and return to the sensor in the form of an echo, which sensormay then compute the distance between itself and the object using thetime that has elapsed between the emission of the signal and thereception of the echo by the sensor.

The use of ultrasonic sensors often requires relatively burdensomenear-sensor signal processing in order to extract the relevantinformation therefrom, depending on the application, such as for exampledistance and angle for object localization, motion type for gesturedetection, validation information in the case of fingerprintrecognition, and diagnostic information in the case of a biomedicalimage.

Various gesture detection solutions have been proposed, such astime-of-flight-based measurement solutions, as described for example in:

R. Nandakumar, V. Iyer, D. Tan, and S. Gollakota, “FingerIO: UsingActive Sonar for Fine-Grained Finger Tracking,” in Proceedings of the2016 CHI Conference on Human Factors in Computing Systems, New York,N.Y., USA, May 2016, pp. 1515-1525, doi: 10.1145/2858036.2858580.

A. Das, I. Tashev, and S. Mohammed, “Ultrasound based gesturerecognition,” in 2017 IEEE International Conference on Acoustics, Speechand Signal Processing (ICASSP), March 2017, pp. 406-410, doi:10.1109/ICASSP.2017.7952187.

-   K. Ling, H. Dai, Y. Liu, and A. X. Liu, “UltraGesture: Fine-Grained    Gesture Sensing and Recognition,” in 2018 15th Annual IEEE    International Conference on Sensing, Communication, and Networking    (SECON), June 2018, pp. 1-9, doi: 10.1109/SAHCN.2018.8397099.

Other gesture detection solutions, based on Doppler measurements, havebeen proposed, as described for example in:

W. Wang, A. X. Liu, and K. Sun, “Device-free gesture tracking usingacoustic signals,” in Proceedings of the 22nd Annual InternationalConference on Mobile Computing and Networking, New York, N.Y., USA,October 2016, pp. 82-94, doi: 10.1145/2973750.2973764.

S. Yun, Y.-C. Chen, and L. Qiu, “Turning a Mobile Device into a Mouse inthe Air,” in Proceedings of the 13th Annual International Conference onMobile Systems, Applications, and Services, New York, N.Y., USA, May2015, pp. 15-29, doi: 10.1145/2742647.2742662.

X. Li, H. Dai, L. Cui, and Y. Wang, “SonicOperator: Ultrasonic gesturerecognition with deep neural network on mobiles,” in 2017 IEEESmartWorld, Ubiquitous Intelligence Computing, Advanced TrustedComputed, Scalable Computing Communications, Cloud Big Data Computing,Internet of People and Smart City Innovation(SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI), August 2017, pp. 1-7, doi:10.1109/UICATC.2017.8397483.

E. A. Ibrahim, M. Geilen, J. Huisken, M. Li, and J. P. de Gyvez, “LowComplexity Multi-directional In-Air Ultrasonic Gesture Recognition Usinga TCN,” in 2020 Design, Automation Test in Europe Conference Exhibition(DATE), March 2020, pp. 1259-1264, doi: 10.23919/DATE48585.2020.9116482.

Existing ultrasonic sensors however have complex architectures and aresubject to high constraints in terms of dimensioning the components(noise, distortion). Furthermore, they generally implement complexsignal-processing steps, such as a fast Fourier transform (FFT) step, acorrelation step, a non-linear filtering step, etc. This results in avery high computing time, consumption and calculation time. Moreover,existing ultrasonic sensors have to store intermediate representationsof the signal, thereby increasing the hardware resources required.

The ultrasonic technique of ultrasonic transducers for measuring time offlight is not sensitive to the same objects as other techniques (radar,optical) (for example, an ultrasonic wave will be reflected by atransparent glazing).

Moreover, the ultrasonic signal of a single ultrasonic transducer isgenerally very nondirectional, the ultrasonic wave being emitted orreceived within an emission cone with an angle typically of several tensof degrees. This means that the processing of the emitted signalprovides an object location with a great amount of angular uncertaintywhen an ultrasonic sensor is used.

To improve the angular resolution of ultrasonic transducer systems, ithas been proposed to use triangulation and beamforming techniques.Triangulation methods consist in measuring distance from two (or more)distinct locations. The intersection of two (or more) items ofinformation makes it possible to locate an object with improvedprecision. However, to be effective, the two pairs of sources/detectorshave to be well spaced from one another, this not always being possibleor desirable in practice, and possibly posing integration problems.

The beamsteering/beamforming approach denotes a set of complextechniques that make it possible respectively to adjust thecharacteristics of the ultrasonic beam at emission (“beamsteering”), orto improve the quality of the information measured at reception(“beamforming”). Such a set of techniques is based on the constructionof interference between the signals of a set of transducers thatsends/measures the signal with a temporal phase offset, whichcorresponds to the reception/emission angle of the plane wave.

In the case of a conventional “beamsteering” technique, the varioustransducers of the set of ultrasonic transducers emit signals with atemporal phase offset, such that the acoustic waves generated by thevarious transducers are constructive, in at least one particulardirection, and destructive in the other directions. Multiple emissionswith different phase offsets are generally used. Measuring the echoescorresponding to these various emissions makes it possible to improveangular resolution. In the case of “beamforming”, a single measurementat reception of the set of transducers may give rise to various signalprocessing operations, corresponding to various types of interference,each corresponding to an observation direction. It is then possible todetermine the angular position of the object. In contrast totriangulation, “beamforming” techniques require the various transducersto be located very close, with a distance between the transducers ofless than a half-wavelength of the signal. By default, the system hasartefacts, that is to say an unwanted emission/sensitivity in certaindirections. Such artefacts greatly worsen the performance of the system(presence of network lobes in the directivity pattern of the ultrasonicsensor, due to spatial aliasing).

To the extent that such a measurement principle is based on inter-signalinterference, it is important for the various signals to be at the samefrequency. In practice, due to the inhomogeneity of the characteristicfrequencies of the ultrasonic transducers of one and the same set oftransducers, ultrasonic systems, in particular those implementingbeamforming techniques, use signals containing primarily a relativelylengthy steady state, since the frequency of the signal in steady statedoes not depend on the characteristic frequency of the transducer, andthe signal-to-noise ratio is more favourable in steady state. Inaddition, a lengthy signal makes it possible to improve the performanceof matched filters that are conventionally used. However, if emissionand reception are performed by the same transducer(s), the twooperations might not be performed at the same time, meaning that thesystem is “blind” for the duration of the emission. When emission andreception are performed by different transducers, the system isgenerally also blind, since the emission signal may interfere with thereception signal via mechanical or electrical coupling, unlessdecoupling is present, which is complex to implement. The “blind region”of the component typically corresponds to a propagation duration ofaround 1 ms. In air (speed of sound=300 m/s), this corresponds to around trip distance of a few tens of centimetres. It is thereforedifficult to use “beamforming” techniques to measure distances shorterthan this distance.

Another drawback of “beamforming” lies in the complexity of theprocessing operations that it implements, in particular when suchprocessing operations have to be embedded or performed in real time.

There is therefore a need for an improved device and an improved methodfor processing signals from a set of ultrasonic transducers.

SUMMARY OF THE INVENTION

To this end, what is proposed is a processing system for processingsignals delivered by an ultrasonic sensor, the ultrasonic sensorcomprising a set of transducers, at least some of the transducers of theset of transducers being configured so as to emit signals and/or receiveechoes corresponding to the reflection of the signals by a detectedobject, signals being transmitted by a plurality of transducers of theultrasonic sensor to the processing system in response to the receptionof echoes by said transducers, the processing system being configured soas to determine at least one characteristic item of information relatingto the detected object, based on the signals received from thetransducers of the ultrasonic sensor. Advantageously, the processingsystem comprises a coupling device configured so as to transform thesignals received from at least some transducers of the set oftransducers into pulses, and a pulse processing unit configured so as toprocess the pulses delivered by the coupling device.

The coupling device comprises:

a thresholding unit configured so as to apply, for each signal receivedfrom a transducer, thresholding to a signal derived from said signalreceived from the transducer, so as to extract directional informationcontained in the phase of the derived signal, using at least onethreshold, the extracted information comprising the rising and/orfalling edges of the derived signal;

a signal-to-pulse transformation unit configured so as to transform thesignal derived from the signal received from the transducer into pulsescontaining the phase of the signal, using the one or more signal edgesextracted by the thresholding unit.

The pulse processing unit is configured so as to determine at least onecharacteristic item of information relating to the detected object basedon the pulses determined by the coupling device for all of the signalsreceived from the transducers.

In one embodiment, the pulse processing unit comprises at least oneclassifier.

In one embodiment, said at least one classifier may comprise a mainclassifier, the main classifier being a pulsed neural network classifieror a non-event-driven classifier.

In one embodiment, said at least one classifier may furthermore comprisea secondary classifier for determining the amplitude of the thresholdused by the thresholding unit from among a set of possible thresholdamplitude values based on the pulses received from the coupling device.

In one embodiment, the processing system may furthermore comprise a setof amplifiers, the set of amplifiers comprising at least one amplifierand being configured so as to amplify the analogue voltage of eachsignal received from the transducer.

The processing system may furthermore comprise a set of bandpassfilters, the set of bandpass filters comprising at least one bandpassfilter and being configured so as to filter the voltage amplified by theset of amplifiers so as to eliminate noise outside the passband, thesignal derived from each signal received from the transducer being thesignal delivered by the set of bandpass filters.

In some embodiments, the processing system may comprise a controllerconfigured so as to adapt one or more shaping parameters of the signalsreceived from the transducers based on one or more adaptation criteriausing signals coming from the pulse processing unit.

In particular, the controller may be configured so as to adapt thethreshold used by the thresholding unit based on the distance betweenthe ultrasonic sensor and the object, or based on the quality ofprevious measurements performed by the ultrasonic sensor, the qualitybeing computed in the pulse domain or after converting the pulse densityinto a real number.

In one embodiment, the pulse processing unit may comprise a set ofcoherence detectors comprising at least one coherence detector and acharacteristic information determination unit, the set of coherencedetectors being configured so as to detect whether the signals comingfrom the transducers, for a given direction of the echoes coming fromthe object, are coherent based on the pulses delivered by the into-pulsetransformation unit, and to deliver said pulses to the characteristicinformation determination unit if coherence is detected.

The characteristic information determination unit may be a unit formeasuring the distance and/or the direction of the echoes coming fromthe object.

In one embodiment, the characteristic information determination unit maybe a classifier.

In one embodiment, a coherence detector may comprise a leaky integratorfor measuring an alignment of the edges of the signals received from thetransducers of the set of transducers.

A coherence detector may comprise a windowing unit configured so as toapply windowing in order to detect coherence between the signalsreceived from the transducers based on the pulses delivered by thecoupling device, the windowing unit being configured so as to count thenumber of pulses, from among all of the transmission channelscorresponding to the various transducers of the set of transducers,within a window of given width.

In some embodiments, the processing system may furthermore comprise alow-pass filter at the output of the set of coherence detectorsconfigured so as to provide an image of the density of the pulsesdelivered by the set of coherence detectors and a sampling unitconfigured so as to sample the low-frequency signal received from thelow-pass filter.

The processing system may furthermore comprise an asynchronous counterarranged at the output of the set of coherence detectors configured soas to count the pulses and sample the output of the set of coherencedetectors with a clock signal.

In one embodiment, the processing system may furthermore comprise amotion detector arranged at the output of the set of coherence detectorsin order to detect the presence of motion in the region monitored by theultrasonic sensor.

Also provided is a method for processing signals delivered by anultrasonic sensor, the ultrasonic sensor comprising a set oftransducers, at least some of the transducers of the set of transducersemitting signals and/or receiving echoes corresponding to the reflectionof the signals by a detected object, the method comprising determiningat least one characteristic item of information relating to the detectedobject, based on the signals received from the transducers of theultrasonic sensor. Advantageously, the method comprises a step oftransforming the signals received from at least some transducers of theset of transducers into pulses, and a step of processing the pulses, thetransformation step comprising, for each signal received from atransducer:

applying thresholding to a signal derived from said signal delivered bythe transducer, so as to extract directional information contained inthe phase of the derived signal using at least one threshold, theextracted information comprising the rising and/or falling edges of thederived signal;

transforming the signal derived from the signal received from thetransducer into pulses containing the phase of the signal, using the oneor more signal edges extracted in the step of applying thresholding,

the step of processing the pulses comprising determining characteristicinformation based on the pulses determined for all of the signalsreceived from the transducers.

The embodiments of the invention thus make it possible to couple thetransducers of an ultrasonic sensor and a pulse processing unit (pulsedneural network for example) using simplified coupling adapted to thedimensioning constraints of the components (noise, distortion). Suchcoupling advantageously makes it possible to replace complexsignal-processing steps (FFT, correlation, non-linear filtering, etc.)with simple operations (delay, sum, scalar product). This results innumerous advantages, including notably:

-   -   a drastic reduction in consumption and computing time;    -   elimination of the storage of intermediate representations of        the signal;    -   an improvement in the compromise between complexity and quality        of the information given by the processing system.

The present invention thus provides coupling of ultrasonic transducerswith a pulse processing unit that allows information contained in theinitial signal from the transducers to be delivered in an optimizedmanner (notably more quickly, more reliably, with less energyconsumption and less time consumption).

BRIEF DESCRIPTION OF THE DRAWINGS

Other features, details and advantages of the invention will becomeapparent on reading the description, which is given with reference tothe appended drawings, which are given by way of example and in which,respectively:

FIG. 1 is a diagram showing one example of an operational system using aprocessing system for processing signals from a set of ultrasonictransducers, according to some embodiments of the invention;

FIG. 2 is a diagram illustrating various states of an ultrasonic signalof short duration (“burst”);

FIG. 3 is a diagram illustrating a phase offset as a function of theangle of incidence of the received echo;

FIG. 4 is a diagram illustrating the matched filter principle, whichmakes it possible to compute the time of flight by correlating theemitted signal with the received signal;

FIG. 5 is a diagram of the processing system, in which the pulseprocessing unit comprises a pulsed neural network classifier, accordingto a first embodiment;

FIG. 6 illustrates the typical electronic excitation signal of atransducer, consisting of multiple successive signals;

FIG. 7 illustrates the transformation of the input signal into pulsescontaining the phase of the signal using the rising edge afterthresholding, according to one embodiment;

FIG. 8 shows one embodiment in which the pulse processing unit comprisesa main classifier used for gesture detection and a secondary classifierused for threshold selection;

FIG. 9 is a diagram of the processing system, in which the pulseprocessing unit comprises a set of coherence detectors, according to asecond embodiment;

FIG. 10 illustrates coherence detection with a leaky integrator,according to one embodiment of the invention;

FIG. 11 illustrates windowing-based coherence detection according to oneembodiment of the invention;

FIG. 12 illustrates the simultaneous outputs of a coherence detector indirections of angles α and 0°, according to one exemplary embodiment;

FIG. 13 is a diagram of the processing system, in which the pulseprocessing unit comprises a pulsed neural network, according to a thirdembodiment;

FIG. 14 is a diagram of the object detection system using a coherencedetector and a non-event-driven classifier;

FIG. 15 is a diagram of the object detection system using a coherencedetector, a non-event-driven classifier and a motion detector, accordingto a fourth embodiment;

FIG. 16 shows a distance matrix with frame-by-frame differentiation andmotion detection;

FIG. 17 is a flowchart showing the method for processing signals from aset of ultrasonic transducers.

DETAILED DESCRIPTION

FIG. 1 shows one example of an operational system 200 using anultrasonic sensor 1 comprising a set of ultrasonic transducers 10 and aprocessing system 100 for processing signals from the transducers 10 ofthe ultrasonic sensor 1, according to some embodiments of the invention.

The set of transducers 10 of the ultrasonic sensor comprises at leasttwo ultrasonic transducers.

The processing system comprises a coupling device 3 and a pulseprocessing unit 2. The coupling device 3 is configured so as to couplethe transducers 10 of the ultrasonic sensor 1 with the pulse processingunit 2.

The set of ultrasonic transducers 10 may comprise a subset of emissiontransducers 1-TX and a subset of reception transducers 1-RX. As avariant, the same transducers 10 may be used at emission and atreception.

The transducers 10 may for example be MEMS transducers.

Advantageously, the ultrasonic transducers 10 of the set of transducers1 may be located at the same location, thereby guaranteeing compactnessof the system.

In one embodiment, the pulse processing unit may comprise a classifier 2such as an SNN pulsed neural network or a non-event-driven classifier(for example a convolutional neural network or any other classifier).

As used here, the term “non-event-driven classifier” refers to anyclassifier implementing non-event-based classification other than apulsed neural network. A non-event-driven classifier uses arepresentation of the datum in the form of a sequence of real valuesrather than in the form of pulses in which the information is containedin their number and position. Some examples of non-event-drivenclassifiers comprise, without limitation, formal neural networks (forexample recurrent neural networks), classifiers based on GMM (acronymfor “Gaussian mixture model”) algorithms followed by a hidden Markovmodel (HMM), SVM (acronym for “support vector machine”) algorithms,logistic regression algorithms, algorithms based on decision treemodels, or else classifiers using rules predefined without learning (notlearned automatically). Some exemplary implementations of the classifiermay be a recurrent neural network, a Gaussian mixture model (GMM)followed by a hidden Markov model (HMM), or a set of rules predefinedwithout learning.

Signals (emitted signals 40) are initially sent by the ultrasonictransducers 10. Such signals are ultrasonic. When these signalsencounter an object 5 (detected object), echoes are formed and reflected(reflected signals 41) to the set of transducers 10. The reflectedsignals 41 reflected by the object 5 and received by the set oftransducers 1 (received signal) are then processed by the processingsystem 100 in order to determine characteristic information relating tothe detected object, depending on the application of the invention. Thecharacteristic information may comprise for example the distance betweenthe ultrasonic sensor 1 and the object, in an object detectionapplication.

The processing system 100 according to the embodiments of the inventionis advantageously configured so as to take advantage of the fact thatthe physical signal at the output of the ultrasonic transducers 10 isrelatively close to what is expected at the input of the pulseprocessing unit 2 (SNN neural network for example).

The processing system 100 may be used in various applications, such as,for example and without limitation, in object detection (detecting thedistance and/or the angle of a detected object), gesture detection, orelse for pattern recognition in images formed based on ultrasonicsignals.

For example, in an application of the invention to object distancedetection, object angle detection or gesture detection, the processingsystem 100 may be used to determine characteristic information relatingto the detected object by performing time-of-flight measurements orDoppler measurements.

In such an application, the propagation of a physical signal is used tocharacterize an object 5 located at a distance. When the emitted signals40 emitted by the ultrasonic sensor 1 encounter an object, the reflectedsignals 41 reflected by the object (echoes) and received by thetransducers 10 may be measured at a later time using signal processingdesigned to determine the distance between the source of the signals,corresponding to the set of ultrasonic transducers 10, and the object 5encountered by the emitted signals, using a “time-of-flight”measurement.

In one application of the invention, the characteristic informationrelating to the detected object, determined by the pulse processing unit2 of the processing system 100, may comprise the distance d between theset 1 of ultrasonic transducers and the detected object. In such anapplication, the distance d may be determined based on the time T_(vol)between the start of the emission of the ultrasonic signal from thesensor 1 (set of signals emitted by the transducers 10) and the start ofthe echo received by the sensor 1 (set of signals reflected by thetransducers 10), using an equation dependent on the time of flightT_(vol), such as for example equation (1):

$\begin{matrix}{d = \frac{cT_{vol}}{2}} & (1)\end{matrix}$

The factor 2 present in the denominator of equation (1) takes intoaccount the round trip of the echo, assuming that the emitter(ultrasonic transducers 10) is close to the receiver (detected object5). In equation (1), c denotes the propagation speed of the acousticwaves in the medium under consideration.

Other techniques for measuring the distance d may be used by the pulseprocessing unit 2 to determine the distance d information, such as forexample a distance measurement using frequency-modulated continuousemission, or an FMCW radar measurement.

In another application of the invention, the characteristic informationdetermined by the pulse processing unit 2 of the processing system 100may comprise the radial speed of the object 5. In such an application,the processing system 100 may use a Doppler radial speed measurement,which provides the radial speed rather than the position of the object(distance and/or angle of the object), for example for a gesturedetection application. Such a Doppler measurement approach is based on:

emission of a signal at a fixed frequency f₀;

reflection from a moving object moving at a radial speed v, such as forexample a hand performing a gesture, which creates echoes at a frequencyf₀+Δf:

$\begin{matrix}{{\Delta f} = {\frac{v}{c}f_{0}}} & (2)\end{matrix}$

sequence and frequency signature in various directions, allowing thegestures to be differentiated.

The emission of the ultrasonic signal emitted by an ultrasonic sensor 1may consist of multiple components at multiple frequencies.

FIG. 2 illustrates various states of a short ultrasonic signal(“burst”).

FIG. 2 corresponds to a signal emitted by an ultrasonic transducer 10excited by an electrical signal of fixed frequency and amplitude. Theelectrical signal consists of a set of sinusoids, with just one and thesame frequency, while the ultrasonic signal consists of a firsttransient excitation state (1), a steady state (2) and a secondtransient de-excitation state (3). The states (1) and (2) areimplemented at a characteristic frequency of the ultrasonic transducer10, also called “characteristic frequency” below. The characteristicfrequency depends on the natural frequency of the transducer 10 and onits quality factor. The second transient state (3) has a sinusoidalsignal at the excitation frequency. The difference between the twofrequencies of interest is typically a few percent (%). The duration ofthe transient states is proportional to the quality factor of thetransducer. For example, for a quality factor of 50, 100 cycles aregenerally needed to reach the steady state (2), this typicallycorresponding to 1 ms for a frequency of around 100 kHz. The processingsystem 100 is advantageously configured so as to take account of thisdifference of a few percent (%) and the significance of the transientstate. Specifically, in the particular case of very short ultrasonicsignals (<1 ms), the signal consists mainly of the two transient states(1) and (3). The frequency of the signal depends on the characteristicfrequency of the transducer. It is therefore difficult to produceinterference between the signals from various transducers. The couplingdevice 3 advantageously transforms the signal into pulses and performsthresholding so as to be more robust to this frequency dispersion.

It should be noted that the electrical signal emitted by a transducerand the resulting ultrasonic signal may be more complex. However, thelimited passband of the ultrasonic transducer 10 means that theultrasonic signal has two transient states whose characteristics dependnot only on the emission signal but also on the natural characteristicsof the transducer 10.

FIG. 3 illustrates the phase offset as a function of the angle ofincidence of the received echo, using three transducers M₀, M₁ and M₂.In the example of FIG. 3, the signal arrives with an angle of incidencea on the set of N transducers (10). The difference in distance coveredby the signal to arrive at the transducers M₀ and M₂, separated by 2d,is equal to 2d sin α.

The acoustic wave propagates at the speed of sound c. The timedifference δ_(t) between the signal received by M₀ and M₂ is thereforeequal to:

$\begin{matrix}{\delta_{t} = \frac{2d\sin\alpha}{c}} & (3)\end{matrix}$

The information is contained in the time difference, that is to say inthe phase offset of the signal.

The signals received by the transducers 10 of the ultrasonic sensor 1are processed by the coupling device 3 and the pulse processing unit 2in order to determine the one or more characteristic items ofinformation relating to an object 5, depending on the application of theinvention.

In one exemplary application to object detection, the characteristicinformation may for example comprise information indicating whether ornot an object has been detected, or the distance between the sensor 1and the detected object 5, which may be determined based on the receivedsignals 41 received by the transducers 10 by correlating the receivedsignals and the expected signals (the correlation is at a maximum for adelay corresponding to the propagation time). It is possible to send anoptimized signal whose autocorrelation has small secondary lobes inorder to further improve the distance measurement.

FIG. 4 illustrates the matched filtering principle, correlating thesignal emitted by the sensor 1 with the signal received by the sensor 1.

In another exemplary application of the invention to “time-of-flight”systems, the system 100 may be configured so as to determinecharacteristic information corresponding to a dynamic characteristic ofthe object, for example its displacement. The characteristic of theobject may be determined by processing multiple successive staticsignals, by measuring the distance and the angle for multiple successivescenes captured by the ultrasonic sensor 1, and by processing suchmeasurements.

Whereas existing processing systems provide intermediate informationabout the processing, the processing system 100 according to theinvention makes it possible to perform direct and optimized processingby directly providing the characteristic information (for examplemovement from right to left in a gesture detection application), withoutintermediate information.

To make the invention easier to understand, the remainder of thedescription of certain embodiments will be given mainly with referenceto a processing system 100 used for object detection or gesturedetection, by way of non-limiting example.

The processing system 100 is configured so as to determinecharacteristic information (for example detection information such as adirection measurement and distance measurement or a gesture detection)using a simplified circuit comprising the coupling device 3 and thepulse processing unit 2.

The signal processing system 100 is configured so as to process thesignals delivered by the ultrasonic transducers 10 of the ultrasonicsensor 1.

Beforehand, at least some of the transducers 10 of the ultrasonic sensor1 emit signals 40. When these signals reach an object 5, echoes 41 areformed, corresponding to the reflected signals 41 reflected by adetected object 5. The reflected signals 41 received by N transducers 10of the ultrasonic sensor 1 are then transmitted to the processing system100. The processing system 100 is configured so as to process thesignals from the N transducers in order to determine at least onecharacteristic item of information relating to the detected object 5.Each signal from a transducer 10 is received by the coupling device 3and corresponds to a processing channel in the coupling device 3.

The coupling device 3 (also called transformation device) is configuredso as to transform the signals from the N transducers 10 of the set oftransducers 1 into pulses.

The pulse processing unit 2 is configured so as to process the pulsesdelivered by the coupling device 3 in order to determine at least onecharacteristic item of information relating to the detected object.

Advantageously, the coupling device 3 comprises:

a thresholding unit 32 configured so as to apply, for each signal from atransducer 10, thresholding to a signal derived from the signal from thetransducer 10 under consideration, so as to extract directionalinformation contained in the phase of the derived signal, using at leastone threshold, the extracted information comprising the rising and/orfalling edges of the derived signal;

a signal-to-pulse transformation unit 33 configured so as to transformthe signal derived from the signal from the transducer into pulsescontaining the phase of the signal, using the one or more signal edgesextracted by the thresholding unit 32.

The pulse processing unit 2 is configured so as to determine thecharacteristic information relating to a detected object 5 based on thepulses determined by the coupling device for all of the signals from thetransducers 10.

The processing system 100 advantageously has low energy consumption andensures coupling between the ultrasonic transducers of the set oftransducers 1 and the pulse processing unit 2.

FIG. 5 shows a processing system 100 for processing signals from the setof transducers 1, in which the pulse processing unit 2 comprises apulsed neural network classifier 20, arranged at the output of theinto-pulse transformation unit 33, according to a first embodiment.

In such an embodiment, the pulsed neural network 20 is capable, on itsown, of learning an optimum way of adding a delay and of combining thevarious channels associated with the transducers.

FIG. 5 corresponds to one exemplary application of the invention toend-to-end gesture detection 5.

In the example of FIG. 5, the detection system comprises a set ofemission transducers 1-TX comprising a plurality of ultrasonic emissiontransducers 10-TX configured so as to emit an ultrasonic signal at afixed frequency of short duration, such as for example 250 μs at 100 kHz(acoustic signal).

To measure characteristic information relating to an object 5 (in theexample of FIG. 5, the object is a hand) located in the scene covered bythe ultrasonic sensor 1, the measurements may be repeated in accordancewith a time interval. The time interval may be fixed (for example, ameasurement is performed every 10 ms). The characteristic informationrelating to a detected object 5 in the scene of the sensor 1 maycomprise the trajectory of the object. The trajectory of the object 5may then be determined by aggregating the results of the measurementsperformed repeatedly during a time period. The characteristicinformation may furthermore comprise high-level characteristics such asgestures based on the determined trajectory.

In one embodiment, the coupling device 3 of the detection system 100 maycomprise a preprocessing unit 31 forming a front-end electronic portioncomprising a set of amplifiers 311 and/or a set of bandpass filters 312.The preprocessing unit 31 is configured so as to convert the physicalsignal (charge, voltage, etc.), received from each of the N transducers(10-RX in the example of FIG. 5), into an analogue voltage. The set ofamplifiers 311 comprises at least one amplifier and is configured so asto amplify the thus-converted analogue voltage so as to make it moreimmune to noise liable to be added to the signal. The set of bandpassfilters 312 comprises at least one bandpass filter and is configured soas to filter the voltage (where applicable after amplification by theset of amplifiers 311) in order to eliminate noise outside the passband.

In the example of FIG. 5, the thresholding unit 32 is configured so asto apply thresholding to the filtered signal delivered by thepreprocessing unit 31 (signal derived from the signal from each of the Ntransducers) in order to retrieve the directional information containedin the phase of the filtered signal using at least one threshold.

In some embodiments, the thresholding unit 32 may be configured so as toapply thresholding to the signal derived from the signal from each ofthe N transducers so as to retain only the rising edge of the signal. Asa variant, the threshold unit 32 may be configured so as to retain onlythe falling edge or both edges (rising and falling).

The coupling device 3 thus corresponds to the analogue domain, while thepulse processing unit 2 corresponds to the pulse domain and thecontroller 34 corresponds to a mixed-signal domain.

One example of an electronic excitation signal emitted by a transduceris shown in FIG. 6, this signal consisting of multiple successivesignals.

FIG. 7 illustrates the successive steps of transforming the signal fromone of the N transducers (10-RX in the example of FIG. 5) into pulsescontaining the phase of the signal, retaining only the rising edge afterthresholding, implemented by the coupling device 3, in the exemplaryembodiment of FIG. 5. The top graph 7A in FIG. 7 shows the signalreceived from one of the N transducers (10-RX), the central graph 7B inFIG. 7 shows the signal after amplification by the set of amplifiers311, filtering by the set of bandpass filters 312, and thresholding bythe thresholding unit 32. The bottom graph 7C in FIG. 7 shows the dataobtained after transformation into pulses by the transformation unit 33.

In some embodiments, the coupling device 3 of the processing system 100may furthermore comprise a controller 34 configured so as to adapt oneor more shaping parameters of the signals. For example, the controller34 may be configured so as to adapt the threshold used by thethresholding unit 32 in order to determine the phase of the signal, inaccordance with one or more adaptation criteria such as criteriarelating to the distance or to the quality of the signal. In someembodiments, the controller 34 may be configured so as to dynamically orstatically adapt the shaping parameters of the signals from the Ntransducers.

In some embodiments, the parameter controller 34 may be configured so asto adapt the threshold used by the thresholding unit 32 based on thedistance between the ultrasonic sensor 1 and the detected object 5. Forexample, the parameter controller 34 may reduce the value of thethreshold during the measurement in order to adapt it to the reductionin the amplitude of the echo of the signal with distance.

In another embodiment, the parameter controller 34 may be configured soas to adapt the value of the threshold based on the quality of previousmeasurements, computed in the pulse domain or after conversion of thepulse density into a real number.

As a variant, the threshold used by the thresholding unit 32 to obtainthe phase of the signal may be fixed.

The controller 34 may use information provided by the pulse processingunit 2.

For example, in one embodiment, the pulse processing unit 2 maycomprise, in addition to the main classifier, a secondary classifierconfigured so as to determine an optimum amplitude for the thresholdbased on intermediate representations of the information in thetransmission chain, in a pulse or non-pulse domain. In one embodiment,the secondary classifier may determine the amplitude of the thresholdfrom among a set of possible threshold amplitude values. In oneembodiment, the secondary classifier may be a pulsed secondary neuralnetwork (SNN), as illustrated in FIG. 8.

In the embodiments in which the classifier 20 is a non-event-drivenclassifier, the coupling device may furthermore comprise at least onecoherence detector.

FIG. 8 shows one example of a pulse processing unit 2 comprising an SNNneural network main classifier 20 used to determine the characteristicinformation relating to a detected object 5 based on received pulses(for example for gesture detection), and a secondary classifier 200, forexample an SNN neural network, configured so as to select the thresholdto be used by the thresholding unit 32 and transmit the thresholdinformation to the controller 34.

In some embodiments, the controller 34 may furthermore be configured soas to synchronize the various functional blocks of the processing system100 in order to implement relevant feedback. The controller 34 maynotably be configured so as to control the time of sending of the pulses(at emission) and synchronize the emission with the reception in orderto be able to measure the information of interest (for example the timeof flight). The controller 34 may furthermore be configured so as toselect a time interval of interest in which the echoes from objectslocated at a chosen distance interval will be received. In terms offeedback, the controller 34 may retrieve information about anyfunctional block, i.e. about the signal before/after amplification,before/after filtering, before/after thresholding in order todynamically adapt detection parameters. For example, in the embodimentof FIG. 5, a portion of the pulsed neural network 20 is dedicated tochoosing an optimum threshold for the channel measurement.

The pulse transformation unit 33 is configured so as to determine apulse density for each of the N channels corresponding respectively tothe N transducers 10 at the origin of the signals processed by theprocessing system 100. The pulse densities thus determined may be usedat the input of the pulse processing unit 2.

In the embodiment of FIG. 5, the pulse processing unit 2 comprises amain classifier 20 (for example a pulsed neural network) for determiningclassification information based on the pulses delivered by the couplingdevice 3, that is to say without having to involve an intermediaterepresentation of the data. In such an embodiment, the characteristicinformation relating to a detected object 5 comprises classificationinformation, such as for example end-to-end gesture classificationinformation in the embodiment of FIG. 5.

In the embodiment in which the main classifier 20 is a non-event-drivenclassifier, the non-event-driven classifier takes the signal at input,which signal may be processed beforehand by a post-filtering block, inthe form of a frame vector. Upon each frame t, the classifier 20 makes adecision about the nature of the gesture based on the frame and thepreceding frames and potentially the following frames over a certainwindow.

FIG. 9 shows a processing system 100 according to a second embodiment.

In this second embodiment, the components 31, 32, 33 and 34 of theprocessing system 100 are similar to those described with reference toFIG. 5 corresponding to the first embodiment. However, the processingsystem 100 according to the second embodiment differs from the firstembodiment, shown in FIG. 5, in that the pulse processing unit 2comprises, rather than the pulsed classifier 20, a set of coherencedetectors 21 comprising at least one coherence detector, followed by acharacteristic information determination unit 22. The characteristicinformation determination unit 22 is configured so as to determine atleast one characteristic item of information relating to a detectedobject 5 detected by the ultrasonic sensor 1 (for example distanceand/or direction of the one or more echoes coming from various objectsin the scene captured by the ultrasonic sensor 1).

The set of coherence detectors 21 uses the directions of incidence ofthe echoes coming from the various objects in the scene captured by theultrasonic sensor 1.

To verify that an echo is coming from a given direction of incidence, asillustrated in FIG. 3, it is verified that the signals of the N emissionchannels corresponding to the N transducers are in phase, if applying atheoretical phase offset associated with this direction, as defined byequation 2. The set of coherence detectors 21 is configured so as toprovide, in parallel, coherence information for M directions based onthe N channels corresponding respectively to the N transducers.

The output of a coherence detector 21 has a certain pulse density at atime t depending on whether the signals received in this direction arecoherent. The set of coherence detectors 21 thus detect whether or notthe signals received in a direction are coherent.

In one embodiment, a coherence detector 21 may comprise a leakyintegrator LIF for measuring the alignment of the edges of the signalscorresponding to the N respective channels corresponding to the Ntransducers.

FIG. 10 illustrates coherence detection implemented by the set ofcoherence detectors 21 using a leaky integrator (leakyintegrate-and-fire), considering an example of M=2 directions (0° and α)and M=3 transmission channels, corresponding to the use of threeemission transducers M₀, M₁ and M₂. Assuming that the echo comes fromthe direction of angle α, and not applying any delay to the channels, itmay be observed that the three signals corresponding to the threechannels associated respectively with the three transducers M₀, M₁ andM₂ have edges that are not aligned, as shown in the left-hand graph inFIG. 10. The edges would be aligned if the direction of incidence wereto be 0°. By applying the theoretical phase offset associated with thedirection of angle α, the edges become aligned, as shown in theright-hand graph in FIG. 10.

The expression of a leaky integrator LIF in the discrete time domain isgiven in equation (3).

$\begin{matrix}\left\{ \begin{matrix}{a_{n} = {{ka_{n - 1}} + x_{n}}} \\{{y_{n} = {{1{if}a_{n}} \geq \theta}},{0{otherwise}}}\end{matrix} \right. & (3)\end{matrix}$

In equation (3):

-   -   x_(n) denotes the pulse train received at input of the LIF        (corresponding to the output of the signal-to-pulse        transformation unit 33),    -   a_(n) denotes the activation parameter of the LIF,    -   y_(n) denotes the output of the LIF,    -   the coefficient k is positive and strictly less than 1, and    -   θ denotes the coherence threshold (the coherence threshold is        distinct from the threshold applied by the thresholding unit        32).

If the activation parameter a_(n) is greater than or equal to thecoherence threshold 9, the output of the LIF y_(n) takes the value 1,this meaning that coherence is detected between the signalscorresponding to the N channels for a given direction.

In some embodiments, the LIF may also be implemented in continuous timewith an analogue implementation, using a similar operating principle.Equation (3) is then replaced with an equation that is a function oftime rather than being a recurrence equation.

The set of coherence detectors 21 has the advantage of being able tooperate even if the various signals to be compared (signalscorresponding to the N channels) have different amplitudes, this beingthe case if the signal is in transient state or if the transducers 10are different from one another. Such coherence detection processing istherefore robust to a certain technological variability.

Furthermore, the set of coherence detectors 21 operates even if thesignals do not have exactly the same frequency, for example in transientstate.

In one variant embodiment, the set of coherence detectors 21 maycomprise a windowing unit configured so as to apply windowing, ratherthan an LI F for detecting the coherence between the signals based onthe received pulses.

Windowing-based coherence detection consists in counting the number ofpulses, from among all of the N contained input channels, within awindow of small width. Similarly to the embodiment in which thecoherence detectors use an LIF, a coherence threshold may be used todetect coherence between the signals corresponding to the N channels fora given direction. The coherence threshold is then applied to the numberof pulses detected within the window that starts upon the first pulse.

FIG. 11 illustrates coherence detection implemented by the set ofcoherence detectors 21 using windowing, according to such an embodiment.

A window is applied at the detection of each rising edge.

The set of coherence detectors 21 provides an output in the form of aplurality of series of pulses. The pulses may be provided directly to apulsed classifier 20 (SNN). If the classifier 20 is a non-event-drivenclassifier, the pulses are converted into a pulse density before beingtransmitted to the classifier 20. The conversion may be performed usinga post-processing block comprising a low-pass filter or a counter forcounting the number of pulses per time interval (for example 10 ms). Thegreater the pulse density determined by the coupling device 2 at a giventime, the greater the coherence in the signals from the transducers 10of the ultrasonic sensor 1.

The characteristic information determination unit 22 may be configuredso as to determine the direction of the one or more main echoes based onthe output of the coherence detector, as shown in FIG. 12.

FIG. 12 illustrates the density of the pulses delivered by the set ofcoherence detectors 21 as a function of time, in a direction of one ormore echoes of angle α (top graph) and in a direction of one or moreechoes of angle 0° (bottom graph). FIG. 12 highlights the time of flightfor the distance measurement.

An echo coming from a particular direction leads to a pulse density onthe output corresponding to the direction of the echo greater than onthe outputs corresponding to the other possible directions. Byconsidering the average value or the maximum on a measurement of thepulse density for all of the given directions, the one or moredirections of arrival of the echoes may be determined.

FIG. 12 also illustrates the principle of the distance measurement. Byusing the same information as for the direction, the distancemeasurement may be performed at the output of the set of coherencedetectors 21 by applying a pulse density threshold to the pulse density,and by computing the distance using equation (1).

FIG. 13 shows a processing system 100, according to a third embodiment.The processing system 100 according to the third embodiment is similarto the processing system according to the second embodiment shown inFIG. 9, and similarly uses a set of coherence detectors 21. However, itadditionally uses a pulsed neural network classifier 20 configured so asto provide classification information based on the pulses delivered bythe set of coherence detectors. Such a classifier 20 is configured so asto receive the series of pulses delivered by the set of coherencedetectors 21.

The characteristic information determination unit 22 of the detectionsystem 100 according to the second embodiment (FIG. 9) is thus replacedwith the classifier 20 in the third embodiment.

FIG. 14 shows a processing system 100, according to a fourth embodiment.The processing system 100 according to the fourth embodiment is similarto the processing system according to the third embodiment shown in FIG.9, and also uses a set of coherence detectors 21. However, itadditionally uses a non-event-driven classifier 20, configured so as toprovide classification information based on the pulses delivered by theset of coherence detectors 21, preceded by a post-processing block 23.The post-processing block 23 is configured so as to convert the pulsesinto a pulse density before being transmitted to the non-event-drivenclassifier 20. The post-processing block 23 may comprise a low-passfilter at the output of the set of coherence detectors 21 in order toprovide an image of the pulse density, rather than a series of pulses,and a sampling unit for sampling the low-frequency signal provided atthe output of the low-pass filter in order to process the data. As avariant, the post-processing block 23 may comprise an asynchronouscounter arranged at the output of the set of coherence detectors 21 forcounting the pulses and sampling the output of the set of coherencedetectors with a clock signal.

FIG. 15 shows a processing system 100, according to a fifth embodiment.

The processing system 100 according to the fifth embodiment is similarto the processing system of the third embodiment shown in FIG. 13, anduses a set of coherence detectors 21 in the same way. This fifthembodiment corresponds to an application of the invention to gesturedetection. The processing system 100 according to the fifth embodimentfurthermore comprises a motion detector 24 for optimizing consumption.The processing system 100 according to the fifth embodiment is notablyconfigured so as to be activated only when motion is detected by themotion detector 24. This makes it possible to avoid activating gesturedetection in the absence of motion. Specifically, most of the time,there is no motion in front of the sensor 1 in the region of interest(scene observed by the sensor 1), meaning that there is no need in thiscase to determine what gesture has been performed. To reduce theconsumption of the system in such a static environment in which there isno motion in front of the sensor 1, the classifier 20 may be arrangeddirectly at the output of the into-pulse transformation unit 33 or atthe output of the set of coherence detectors 21, as shown in FIG. 15. Inthe example of FIG. 15, the classifier 20 may then perform aclassification in order to detect a gesture when motion is detected bythe motion detector.

Hereinafter, consideration is given to the example of FIG. 15, in whichthe motion detection is performed by the motion detector 24 at theoutput of the set of coherence detectors 21.

The output of the set of coherence detectors 21 may be represented by amatrix B of dimensions T×N×K, where T is the number of measurements orframes, N is the number of samples per frame (time axis in FIG. 12), andK is the number of directions analysed in the set of coherence detectors21. The elements of the matrix B are denoted b_(i,j,k).

The number of directions K is less than or equal to the total number ofdirections M.

The elements of the matrix B correspond to the pulse density within aninterval [t, t+t_(frame)] where t_(frame) denotes the length of a frame.

The motion detector 24 then uses the elements of the matrix B.

The motion detector 24 is configured so as to determine a distancematrix D=[d_(i,j)] by summing the components b_(i,j,k) on the dimensioncorresponding to the directions:

d _(i,j)=Σ_(k=0) ^(K-1) b _(i,j,k)  (4)

The motion may be quantified by examining the difference between twosuccessive frames on the distance matrix. A difference matrixDD=[dd_(i,j)] may then be determined by differentiating the matrix D onthe frame axis:

dd _(i,j) =d _(i,j) −d _(i-1,j)  (5)

A motion predictor p_(i) may then be computed by multiplying the averageand maximum of the difference per frame, using equation (6):

$\begin{matrix}{p_{i} = {\max\limits_{j}{dd}_{i,j} \times \frac{1}{N}{\sum_{j = 0}^{N - 1}{dd}_{i,j}}}} & (6)\end{matrix}$

FIG. 16 illustrates the computing of a motion predictor on real data(distance matrix, frame-by-frame differentiation and motion detection).In the example of FIG. 16, it is possible to observe motion from frame 0to 120 and then no motion thereafter on the distance matrix. Comparingthe motion predictor with a threshold gives a signal that may be used bythe gesture detector 25 to determine a gesture classification.

FIG. 17 illustrates the method for processing signals from a set oftransducers, according to some embodiments.

In step 600, at least some of the transducers of the set of transducersemit signals and/or receive echoes corresponding to the reflection ofthe signals by a detected object 5.

In steps 602 and 604, a step of transforming the signals received fromat least some transducers of the set of transducers into pulses isimplemented.

More precisely, in step 602, for each signal received at reception byone of the N transducers 10, thresholding is applied to a signal derivedfrom the signal received from the transducer, so as to extractdirectional information contained in the phase of the derived signal,using at least one threshold, the extracted information comprising therising and/or falling edges of the derived signal.

In step 604, the signal derived from the signal received from thetransducer is transformed into pulses containing the phase of thesignal, using the one or more signal edges extracted in the step ofapplying thresholding.

In step 606, a step of processing the obtained pulses is implemented,the pulse processing step comprising determining characteristicinformation based on the pulses determined for all of the signalsreceived from the transducers.

The determined characteristic information may then be delivered foradditional processing, or to generate a display of this information. Asa variant, an action may be triggered based on the determinedcharacteristic information.

The embodiments of the invention make it possible to detect objects,gestures or even dynamic characteristics of objects. However, a personskilled in the art will easily understand that the invention may be usedin other applications, for example for fingerprint recognition. In anapplication of the invention to fingerprint recognition, the set oftransducers 1 may be a 2D matrix. Each transducer 10 of the set oftransducers 1 sends a pulse, which is returned if the transducer 10 islocated facing a “cavity” in the hand, and which is transmitted if thetransducer is located facing the skin. The set of returned pulses isused to form an image (at what stage of the processing chain?), which isthen processed by the processing system 100.

The embodiments of the invention thus allow direct coupling of theultrasonic transducers 10 to a pulse processing unit 2 (comprising forexample a neural network), making it possible to directly determine theone or more characteristic items of information, depending on theapplication of the invention.

The processing system 100 according to the embodiments of the inventionis advantageously configured so as to improve angular resolution incomparison with ultrasonic transducer systems from the prior art.

The processing system 100 according to the embodiments of the inventionis configured so as to make it possible to reduce the blind region ofthe transducer system, to reduce the complexity of the processing, andto provide robustness to the dispersion in characteristics of thetransducers 10 of the set of transducers 1, while still having a certaincompactness (the set of transducers 10 is located at the same location)and while providing angular quality information.

More generally, a person skilled in the art will understand that theprocessing device 100 or subsystems of the device according to theembodiments of the invention may be implemented in various ways byhardware, software or a combination of hardware and software, notably inthe form of program code that may be distributed in the form of aprogram product, in numerous forms. In particular, the program code maybe distributed using computer-readable media, which may includecomputer-readable storage media and communication media. The methodsdescribed in the present description may notably be implemented in theform of computer program instructions able to be executed by one or moreprocessors in an information technology computer device. These computerprogram instructions may also be stored in a computer-readable medium.

Moreover, the invention is not limited to the embodiments describedabove by way of non-limiting example. It encompasses all of the variantembodiments that may be contemplated by a person skilled in the art. Inparticular, the invention is not limited to the exemplary applicationsdescribed above by way of example. It applies to other applications invarious fields. For example, in an exemplary application of theinvention to the biomedical field, the processing system 100 may be usedto provide images obtained by ultrasonography representing the echoesreceived by a set of ultrasonic transducers. In some cases, not only thefirst echo but also the following echoes may be represented. Processingthe image makes it possible to extract detection information defineddepending on the biomedical application (for example thickness of thenape of the neck, etc.). The information that is provided may then beused to aid the medical diagnosis. Advantageously, the embodiments makeit possible to simplify the image reconstruction processing operationsfor ultrasonography systems outside laboratories.

1. A processing system for processing signals delivered by an ultrasonicsensor, the ultrasonic sensor comprising a set of transducers, at leastsome of the transducers of the set of transducers being configured so asto emit signals and/or receive echoes corresponding to the reflection ofsaid signals by a detected object, signals being transmitted by aplurality of transducers of the ultrasonic sensor to the processingsystem in response to the reception of echoes by said transducers, theprocessing system being configured so as to determine at least onecharacteristic item of information relating to the detected object,based on the signals received from the transducers of the ultrasonicsensor, comprising a coupling device configured so as to transform thesignals received from at least some transducers of the set oftransducers into pulses, and a pulse processing unit configured so as toprocess the pulses delivered by the coupling device, and in that thecoupling device comprises: a thresholding unit configured so as toapply, for each signal received from a transducer, thresholding to asignal derived from said signal received from the transducer, so as toextract directional information contained in the phase of the derivedsignal, using at least one threshold, the extracted informationcomprising the rising and/or falling edges of the derived signal; asignal-to-pulse transformation unit configured so as to transform thesignal derived from the signal received from the transducer into pulsescontaining the phase of the signal, using the one or more signal edgesextracted by the thresholding unit, the pulse processing unit beingconfigured so as to determine at least one characteristic item ofinformation relating to the detected object based on the pulsesdetermined by the coupling device for all of the signals received fromsaid transducers.
 2. The system according to claim 1, wherein the pulseprocessing unit comprises at least one classifier.
 3. The systemaccording to claim 2, wherein said at least one classifier comprises amain classifier, the main classifier being a pulsed neural networkclassifier or a non-event-driven classifier.
 4. The system according toclaim 2, wherein said at least one classifier furthermore comprises asecondary classifier for determining the amplitude of the threshold usedby the thresholding unit from among a set of possible thresholdamplitude values based on the pulses received from the coupling device.5. The system according to claim 1, further comprising a set ofamplifiers, the set of amplifiers comprising at least one amplifier andbeing configured so as to amplify the analogue voltage of each signalreceived from the transducer.
 6. The system according to claim 5,further comprising a set of bandpass filters, the set of bandpassfilters comprising at least one bandpass filter and being configured soas to filter the voltage amplified by the set of amplifiers so as toeliminate noise outside the passband, said signal derived from eachsignal received from the transducer being the signal delivered by theset of bandpass filters.
 7. The system according to claim 1, comprisinga controller configured so as to adapt one or more shaping parameters ofthe signals received from the transducers based on one or moreadaptation criteria using signals coming from the pulse processing unit.8. The system according to claim 7, wherein the controller is configuredso as to adapt the threshold used by the thresholding unit based on thedistance between the ultrasonic sensor and said object, or based on thequality of previous measurements performed by the ultrasonic sensor,said quality being computed in the pulse domain or after converting thepulse density into a real number.
 9. The system according to claim 5,wherein the pulse processing unit comprises a set of coherence detectorscomprising at least one coherence detector and a characteristicinformation determination unit, the set of coherence detectors beingconfigured so as to detect whether the signals coming from saidtransducers are coherent, for a given direction of the echoes comingfrom the object, based on the pulses delivered by the into-pulsetransformation unit, and to deliver said pulses to the characteristicinformation determination unit if coherence is detected.
 10. The systemaccording to claim 9, wherein the characteristic informationdetermination unit is a unit for measuring the distance and/or thedirection of the echoes coming from the object.
 11. The system accordingto claim 10, wherein the characteristic information determination unitis a classifier.
 12. The system according to claim 9, wherein acoherence detector comprises a leaky integrator for measuring analignment of the edges of the signals received from said transducers ofthe set of transducers.
 13. The system according to claim 9, wherein acoherence detector comprises a windowing unit configured so as to applywindowing in order to detect coherence between the signals received fromsaid transducers based on the pulses delivered by the coupling device,the windowing unit being configured so as to count the number of pulses,from among all of the transmission channels corresponding to the varioustransducers of the set of transducers, within a window of given width.14. The system according to claim 9, further comprising a low-passfilter at the output of the set of coherence detectors configured so asto provide an image of the density of the pulses delivered by the set ofcoherence detectors and a sampling unit configured so as to sample thelow-frequency signal received from the low-pass filter.
 15. The systemaccording to claim 9, further comprising an asynchronous counterarranged at the output of the set of coherence detectors configured soas to count the pulses and sample the output of the set of coherencedetectors with a clock signal.
 16. The system of claim 9, furthercomprising a motion detector arranged at the output of the set ofcoherence detectors in order to detect the presence of motion in theregion monitored by the ultrasonic sensor.
 17. A method of processingsignals delivered by an ultrasonic sensor, the ultrasonic sensorcomprising a set of transducers, at least some of the transducers of theset of transducers emitting signals and/or receiving echoescorresponding to the reflection of said signals by a detected object,the method comprising determining at least one characteristic item ofinformation relating to the detected object, based on the signalsreceived from the transducers of the ultrasonic sensor, wherein themethod comprises a step of transforming the signals received from atleast some transducers of the set of transducers into pulses, and a stepof processing said pulses, the transformation step comprising, for eachsignal received from a transducer: applying thresholding to a signalderived from said signal delivered by the transducer, so as to extractdirectional information contained in the phase of the derived signalusing at least one threshold, the extracted information comprising therising and/or falling edges of the derived signal; transforming thesignal derived from the signal received from the transducer into pulsescontaining the phase of the signal, using the one or more signal edgesextracted in the step of applying thresholding, and in that the step ofprocessing the pulses comprises determining characteristic informationbased on the pulses determined for all of the signals received from saidtransducers.